Advances in Applied Energy最新文献

Planning future charging infrastructure for private EVs: A city-scale assessment of demand and capacity 规划未来私人电动汽车的充电基础设施：城市规模的需求和容量评估

IF 13.8 Q1 ENERGY & FUELS

Advances in Applied Energy

Pub Date : 2025-12-07 DOI: 10.1016/j.adapen.2025.100258

Hong Yuan , Minda Ma , Nan Zhou , Yanqiao Deng , Junhong Liu , Shufan Zhang , Zhili Ma

Capacity planning for electric vehicle (EV) charging infrastructure has emerged as a critical challenge in developing low-carbon urban energy systems. This study proposes the first demand-driven, multi-objective planning model for optimizing city-scale capacity allocation of EV charging infrastructure. The model employs a bottom-up approach to estimate charging demand differentiated by vehicle type—battery electric vehicles (BEVs), extended-range electric vehicles (EREVs), and plug-in hybrid electric vehicles (PHEVs). Chongqing, a rapidly expanding EV industry cluster in China with a strong industrial base, supportive policies, and diverse urban morphologies, is selected as the case study. The results show that (1) monthly EV electricity consumption in Chongqing rose from 18.9 gigawatt-hours (GWh) in June 2022 to 57.5 GWh in December 2024, with associated carbon emissions increasing from 9.9 kilotons of carbon dioxide (ktCO₂) to 30 ktCO₂; (2) 181,622 additional charging piles were installed between 2022 and 2024, with the fastest growth observed in Yubei, reflecting a demand-responsive strategy that prioritizes areas with higher population density, higher income levels, and adequate land availability for pile deployment, rather than broad geographic coverage; and (3) between 2025 and 2030, EV electricity demand is projected to reach 1940 GWh, with the number of charging piles exceeding 1.4 million, and charging demand from EREVs and PHEVs expected to overtake BEVs later in the period. While Chongqing serves as the pilot area, the proposed planning platform is adaptable for application in cities worldwide, enabling cross-regional comparisons under diverse socio-economic, geographic, and policy conditions. Overall, this work offers policymakers a versatile tool to support sustainable, cost-effective EV infrastructure deployment aligned with low-carbon electrification targets in the transportation sector.

电动汽车（EV）充电基础设施的容量规划已成为发展低碳城市能源系统的关键挑战。本文首次提出了城市规模电动汽车充电基础设施容量配置优化的需求驱动多目标规划模型。该模型采用自下而上的方法来估计不同车型（纯电动汽车（bev）、增里程电动汽车（EREVs）和插电式混合动力汽车（phev））的充电需求。重庆是中国快速发展的电动汽车产业集群，拥有强大的产业基础、扶持政策和多样的城市形态。结果表明：(1)重庆市电动汽车月用电量从2022年6月的18.9 GWh增加到2024年12月的57.5 GWh，碳排放量从9.9千吨二氧化碳（ktCO2）增加到30千吨二氧化碳；(2) 2022年至2024年期间，新增充电桩181,622个，其中渝北增长最快，反映了需求响应战略，优先考虑人口密度高、收入水平高、土地可用性充足的地区，而不是广泛的地理覆盖；(3) 2025 - 2030年，电动汽车电力需求预计将达到1940 GWh，充电桩数量将超过140万个，纯电动汽车和插电式混合动力汽车的充电需求预计将在后期超过纯电动汽车。虽然重庆是试点地区，但拟议的规划平台可适用于全球城市，可以在不同的社会经济、地理和政策条件下进行跨区域比较。总的来说，这项工作为政策制定者提供了一个多功能工具，以支持可持续的、具有成本效益的电动汽车基础设施部署，并与交通部门的低碳电气化目标保持一致。

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引用次数: 0

Economics of electric vehicle corridor fast charging in the United States 美国电动汽车走廊快速充电的经济性

IF 13.8 Q1 ENERGY & FUELS

Advances in Applied Energy

Pub Date : 2025-12-06 DOI: 10.1016/j.adapen.2025.100257

Brennan Borlaug , Vince Caristo , Fletcher Ouren , Fan Yang , Eric Wood , Laura Roberson

Corridor direct-current fast charging (DCFC) stations enable long-distance electric vehicle travel, yet their economics remain uncertain due to high capital costs, low initial utilization, and exposure to utility demand charges. This study evaluates the long-term economics of corridor DCFC across the United States, incorporating capital and operating expenses—including charging equipment and real-world utility tariffs—alongside modeled station utilization, financial incentives, and ancillary retail revenue. In the Baseline scenario, modeled breakeven costs for corridor DCFC average $0.42/kWh over 20 years, yet fewer than half of stations reach cost parity with gasoline on a per-mile basis. Utilization is the primary driver of cost variation, with low-utilization stations costing roughly six times more per kilowatt-hour than the national average. Excluding stations that fail to reach cost parity reduces National Highway System coverage within 50 miles from 94% to 67%, underscoring the trade-off between market-driven deployment and comprehensive network coverage. These results provide guidance for charging providers, utilities, planners, and policymakers seeking to develop and sustain a financially viable national corridor charging network.

走廊直流电快速充电站（DCFC）可以实现电动汽车的长途行驶，但由于资本成本高、初始利用率低以及公用事业需求收费，其经济性仍不确定。本研究评估了美国走廊DCFC的长期经济效益，将资本和运营费用（包括充电设备和现实世界的公用事业费率）与模拟站点利用率、财政激励和辅助零售收入结合起来。在基线情景中，走廊dfc的模型盈亏平衡成本在20年内平均为0.42美元/千瓦时，但不到一半的加油站达到每英里成本与汽油相同。利用率是成本变化的主要驱动因素，低利用率电站每千瓦时的成本大约是全国平均水平的六倍。排除那些无法达到成本平价的站点，将使50英里范围内的国家公路系统覆盖率从94%降至67%，强调了市场驱动部署和全面网络覆盖之间的权衡。这些结果为寻求发展和维持财政上可行的国家走廊充电网络的充电供应商、公用事业公司、规划人员和政策制定者提供了指导。

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引用次数: 0

Advancing building stock transformation models: An agent-based approach and its application to Germany 推进存量转换模型：基于主体的方法及其在德国的应用

IF 13.8 Q1 ENERGY & FUELS

Advances in Applied Energy

Pub Date : 2025-11-20 DOI: 10.1016/j.adapen.2025.100256

Şirin Alibaş , Songmin Yu , Mahsa Bagheri , Tobias Fleiter

The building sector is pivotal for achieving climate neutrality, requiring sophisticated modeling tools to guide the energy transition. It is highly heterogeneous with variety in both the built environment and in its decision-makers. While many sectoral models exist, most of them fall short of capturing the barriers and limitations in the energy transition as they lack high spatial resolution and a detailed representation of heterogeneous building characteristics and local infrastructure constraints. To address this gap, we present RENDER-Building, a new agent-based model (ABM) designed for high-resolution analysis of building stock transformation. We validate and apply the model to the German building stock to simulate potential transformation pathways until 2050 under three distinct scenarios. The individual buildings are the agents here with detailed attributes, located in a settlement type in a NUTS3 region. The model explicitly considers the availability of energy infrastructure and simulates agents’ decisions about renovation and technology adoption based on bounded rationality. Our case study’s results indicate that even with ambitious measures, Germany’s building sector may miss its short-term emission targets due to the inertia of the existing stock. A transformation pathway considering realistic challenges could substantially exceed the short- and long-term emission targets, necessitating difficult and potentially costly interventions to get back on track. Our study demonstrates the utility of high-resolution ABMs in providing nuanced, actionable insights for policymakers, helping them to navigate the complexities of the building sector’s energy transition.

建筑行业是实现气候中和的关键，需要复杂的建模工具来指导能源转型。它在建筑环境和决策者方面都是高度异质的。虽然存在许多部门模型，但大多数模型都无法捕捉能源转型中的障碍和限制，因为它们缺乏高空间分辨率和对异质建筑特征和当地基础设施限制的详细表示。为了解决这一差距，我们提出了一种新的基于代理的模型（ABM），用于建筑存量转换的高分辨率分析。我们验证了该模型并将其应用于德国建筑存量，以模拟在三种不同情景下到2050年的潜在转型路径。单个建筑是具有详细属性的代理，位于NUTS3区域的聚落类型中。该模型明确地考虑了能源基础设施的可用性，并基于有限理性模拟了主体关于改造和技术采用的决策。我们的案例研究结果表明，即使采取雄心勃勃的措施，由于现有库存的惯性，德国建筑行业也可能无法实现其短期排放目标。考虑到现实挑战的转型途径可能大大超过短期和长期排放目标，需要采取困难和可能昂贵的干预措施才能回到正轨。我们的研究展示了高分辨率ABMs在为政策制定者提供细致入微、可操作的见解方面的效用，帮助他们应对建筑行业能源转型的复杂性。

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引用次数: 0

A systematic review of technologies, measures, and CO2 emission reduction potential for maritime transport decarbonisation 对海上运输脱碳的技术、措施和二氧化碳减排潜力进行系统审查

IF 13.8 Q1 ENERGY & FUELS

Advances in Applied Energy

Pub Date : 2025-11-07 DOI: 10.1016/j.adapen.2025.100255

Sina Fadaie , Patricia Thornley , Jean-Baptiste Souppez

The maritime shipping sector is a significant contributor to global carbon dioxide (CO₂) emissions, accounting for approximately 2.7%-3% of global emissions. In response, the International Maritime Organization (IMO) has set ambitious targets: a 30% reduction in emissions by 2030, 80% by 2040, and net-zero by 2050, relative to 2008 levels. Meeting these goals requires a comprehensive understanding of the full range of viable decarbonisation measures. Therefore, this study conducts a systematic review of maritime decarbonisation measures, applying the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology. Unlike previous studies, this paper not only provides an updated overview of CO₂ reduction measures but also maps them to specific vessel types based on data reported in the literature. Furthermore, the findings are compared with literature to highlight shifts in mitigation potential. A case study is also included to schematically demonstrate how these measures can be applied in practice. Following a rigorous analysis: (i) thirty-two individual CO₂ mitigation measures were identified and classified into six categories, (ii) alternative fuels shown the highest long-term potential (5–100 % CO₂ emission reduction), whereas hull design improvements show the lowest (1–20 %), (iii) the wide disparity in reported abatement values is attributed to inconsistent system boundaries, variability in fuel origin, partial-blend scenarios, and differing assumptions across studies, (iv) combinations of measures provide the most practical and realistic pathway to phased emissions reduction. These findings are expected to assist decision-makers in selecting effective, context-appropriate strategies to support global maritime decarbonisation and ensure long-term sectoral sustainability.

海运部门是全球二氧化碳（CO2）排放的重要贡献者，约占全球排放量的2.7%-3%。为此，国际海事组织（IMO）制定了雄心勃勃的目标：到2030年减排30%，到2040年减排80%，到2050年实现净零排放。要实现这些目标，就需要全面了解各种可行的脱碳措施。因此，本研究对海事脱碳措施进行了系统审查，应用了系统审查和荟萃分析（PRISMA）方法的首选报告项目。与以往的研究不同，本文不仅提供了二氧化碳减排措施的最新概述，而且根据文献中报道的数据将其映射到特定的船舶类型。此外，将研究结果与文献进行比较，以突出减缓潜力的变化。还包括一个案例研究，以示意性地演示如何在实践中应用这些措施。经过严格的分析：(i)确定了32种单独的二氧化碳减缓措施，并将其分为6类；（ii）替代燃料显示出最高的长期潜力（5 - 100%的二氧化碳减排），而船体设计改进显示出最低的长期潜力（1 - 20%）；（iii）报告的减排值的巨大差异归因于不一致的系统边界、燃料来源的可变性、部分混合情景和不同研究的不同假设。（iv）各项措施的结合为分阶段减少排放提供了最实际和最现实的途径。这些研究结果有望帮助决策者选择有效的、适合具体情况的战略，以支持全球海上脱碳，并确保长期的部门可持续性。

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引用次数: 0

Utilizing oxygen from green hydrogen production in wastewater treatment plant aeration: A techno-economic analysis 利用废水处理厂曝气中绿色制氢产生的氧气：技术经济分析

IF 13.8 Q1 ENERGY & FUELS

Advances in Applied Energy

Pub Date : 2025-11-01 DOI: 10.1016/j.adapen.2025.100254

Levin Matz , Lukas Koenemann , Steffen Brundiers , Inga Beyers , Arne Freyschmidt , Astrid Bensmann , Richard Hanke-Rauschenbach

The growing demand for green hydrogen is driving the expansion of water electrolysis. The resulting oxygen byproduct offers potential added value when used in sectors with high oxygen demand, such as wastewater treatment. This study investigates the techno-economic viability of using electrolysis oxygen to supplement conventional air blowers in the aeration process of municipal wastewater treatment plants (WWTPs) to reduce aeration costs and thereby improve the overall economics of hydrogen production. A comprehensive system model is developed, incorporating renewable electricity supply, water electrolysis, hydrogen compression, storage, and transport, as well as WWTP aeration via conventional air blowers and electrolysis oxygen. Results show that electrolysis oxygen can reduce WWTP aeration costs by up to 68%. If these cost reductions are attributed as a benefit to the hydrogen system, they correspond to hydrogen supply cost savings of up to 0.39 EUR/kgH₂. However, the analysis indicates that economic viability is substantially influenced by factors such as the distance of hydrogen transport from the WWTP to the European Hydrogen Backbone feed-in point, which should not exceed 25 km, and the alignment between the scale of hydrogen production and the size of the WWTP, with cost-effective integration being particularly feasible for larger WWTPs (≥500,000 PE).

对绿色氢日益增长的需求正在推动水电解的扩张。当用于废水处理等高需氧量行业时，所产生的氧气副产品具有潜在的附加值。本研究探讨了在城市污水处理厂（WWTPs）曝气过程中使用电解氧作为常规鼓风机的补充，以降低曝气成本，从而提高制氢的整体经济可行性。开发了一个综合系统模型，包括可再生电力供应、水电解、氢气压缩、储存和运输，以及通过传统鼓风机和电解氧气进行污水处理厂曝气。结果表明，电解氧可使污水处理厂曝气成本降低68%。如果将这些成本的降低归因于氢气系统的效益，则相当于节省了高达0.39欧元/千瓦时的氢气供应成本。然而，分析表明，经济可行性在很大程度上受到诸如从污水处理厂到欧洲氢气骨干进料点的氢气输送距离（不应超过25公里）以及氢气生产规模与污水处理厂规模之间的一致性等因素的影响，对于较大的污水处理厂（≥500,000 PE）而言，成本效益整合尤其可行。

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引用次数: 0

Multimodal ultra-short-term probabilistic solar power forecasting with generative AI and Transformer 基于生成式人工智能和变压器的多模态超短期概率太阳能发电预测

IF 13.8 Q1 ENERGY & FUELS

Advances in Applied Energy

Pub Date : 2025-10-31 DOI: 10.1016/j.adapen.2025.100250

Binyu Xiong , Yuntian Chen , Xin Zhao , Zhongyue Su , Jun Fu , Dali Chen , Dongxiao Zhang

Solar power is one of the most widely adopted forms of renewable energy, with its usage rapidly increasing in recent years. However, solar power generation is highly sensitive to environmental factors, leading to frequent fluctuations. These fluctuations present challenges for large-scale integration into the power grid. Sky images, which provide real-time information about sky conditions, can help improve ultra-short-term solar power forecasting. Nonetheless, due to the inherent uncertainty of cloud movement, solar power generation can be unstable over short time intervals. This instability calls for the inclusion of uncertainty in ultra-short-term forecasting models. Inspired by recent advances in deep learning, we propose a novel framework for ultra-short-term probabilistic solar power generation forecasting. This framework uses both historical solar power generation data and sky images as inputs. First, a video prediction model based on generative artificial intelligence (AI) is applied to generate multiple potential future sky image sequences. Next, a Transformer-based multimodal model combines each predicted sequence with historical solar power generation data to derive a distribution of possible future power outputs. To account for uncertainties in both the video prediction and multimodal models, these distributions are aggregated into a single overall distribution. We conducted experiments on real-world datasets, with prediction times ranging from 15 to 60 min, to compare our method with previous mainstream approaches. The results demonstrate that our method outperforms existing approaches in both deterministic and probabilistic forecasting tasks. In the 15 min ahead forecasting task, compared to the method using only historical solar power generation data, our method reduces the Root Mean Square Error (RMSE) of the deterministic evaluation metric by 20.6% and the Continuous Ranked Probability Score (CRPS) of the probabilistic evaluation metric by 19.4%. When compared to the method using only sky image data, our approach reduces the RMSE by 47.3% and the CRPS by 51.3%. Furthermore, we conduct additional analysis on the performance of various methods under different weather conditions.

太阳能是最广泛采用的可再生能源之一，近年来其使用量迅速增加。然而，太阳能发电对环境因素高度敏感，导致波动频繁。这些波动对大规模并入电网提出了挑战。天空图像提供了关于天空状况的实时信息，可以帮助改进超短期太阳能预测。然而，由于云层运动的固有不确定性，太阳能发电在短时间间隔内可能不稳定。这种不稳定性要求在超短期预测模型中包含不确定性。受深度学习最新进展的启发，我们提出了一个超短期概率太阳能发电预测的新框架。该框架使用历史太阳能发电数据和天空图像作为输入。首先，应用基于生成式人工智能（AI）的视频预测模型生成多个潜在的未来天空图像序列。接下来，基于变压器的多模态模型将每个预测序列与历史太阳能发电数据结合起来，得出可能的未来功率输出分布。为了考虑视频预测和多模态模型中的不确定性，这些分布被汇总成一个整体分布。我们在真实世界的数据集上进行了实验，预测时间从15到60分钟不等，将我们的方法与之前的主流方法进行了比较。结果表明，我们的方法在确定性和概率预测任务中都优于现有的方法。在提前15分钟预测任务中，与仅使用历史太阳能发电数据的方法相比，我们的方法将确定性评价指标的均方根误差（RMSE）降低了20.6%，将概率评价指标的连续排序概率得分（CRPS）降低了19.4%。与仅使用天空图像数据的方法相比，我们的方法将RMSE降低了47.3%，CRPS降低了51.3%。此外，我们还对各种方法在不同天气条件下的性能进行了额外分析。

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引用次数: 0

Enhancing the feasibility of direct air capture by utilizing environmental variability 利用环境变异性提高直接空气捕获的可行性

IF 13.8 Q1 ENERGY & FUELS

Advances in Applied Energy

Pub Date : 2025-10-30 DOI: 10.1016/j.adapen.2025.100253

Kuihua Wang , Lijun Zhu , Junye Wu , Tianshu Ge

A primary challenge impeding the large-scale deployment of direct air capture (DAC) is its high energy consumption, mainly associated with external input to drive process parameter swings (such as temperature, humidity, and CO₂ concentration). Environmental parameter exhibits strong spatiotemporal variability, significantly impacting the performance of DAC. By adapting DAC operation with environmental variability, potential energy can be effectively extracted from air, thus lowering the energy demand. Diurnal fluctuations can be leveraged for passive desorption, while intense wind facilitates the passive adsorption, Seasonal and long-term environmental changes necessitate adaptive scheduling and operational optimization to maintain performance. Geographical disparities in climate act as natural energy reservoirs, offering opportunities for region-specific deployment strategies. Particularly, high ambient temperatures enable efficient integration of air-source heat pumps; cold climates suppress water co-adsorption and provide effective condensation; humid regions employ water-source heat pump to recovery excessive condensation heat efficiently; and arid regions, with low humidity, minimize water desorption requirements. Future research should prioritize the practical experimental testing, adaptive control and optimization algorithms, alongside establishing quantitative assessment frameworks to guide climate-specific deployment.

阻碍直接空气捕获（DAC）大规模部署的主要挑战是其高能耗，主要与驱动工艺参数波动（如温度、湿度和二氧化碳浓度）的外部输入有关。环境参数表现出强烈的时空变异性，显著影响DAC的性能。通过使DAC操作适应环境的可变性，可以有效地从空气中提取势能，从而降低能源需求。可以利用日波动进行被动解吸，而强风促进被动吸附，季节性和长期的环境变化需要自适应调度和操作优化来保持性能。气候的地理差异是天然的能源储藏库，为特定区域的部署战略提供了机会。特别是，高环境温度使空气源热泵能够有效地集成；寒冷的气候抑制水的共吸附，提供有效的冷凝；潮湿地区采用水源热泵高效回收过多冷凝热；而干旱地区，湿度低，最大限度地减少水的解吸需求。未来的研究应优先考虑实际的实验测试、自适应控制和优化算法，并建立定量评估框架，以指导针对气候的部署。

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引用次数: 0

Assessing the techno-economic impact of district heating on electrical distribution grid reinforcements 评估集中供热对配电网加固的技术经济影响

IF 13.8 Q1 ENERGY & FUELS

Advances in Applied Energy

Pub Date : 2025-10-29 DOI: 10.1016/j.adapen.2025.100251

Jerry Lambert , Hermann Kraus , Markus Doepfert , Miaomiao He , David Gschossmann , Amedeo Ceruti , Isabell Nemeth , Oliver Brückl , Thomas Hamacher , Hartmut Spliethoff

Enhanced sector coupling across electricity, mobility, and heating sectors leads to higher efforts for distribution grid upgrades. Based on a case study, this paper evaluates the role of district heating networks in reducing electrical distribution grid reinforcements and compares their economic viability against a building-specific heat supply using heat pumps. A detailed energy system model is used to analyze two building energy renovation scenarios: a business-as-usual scenario with a 1 % annual renovation rate and an ambitious scenario with a rate of 2 %. Using a two-step optimization, the impact of different district heating network penetration levels on the distribution grid is evaluated, followed by an ex-post analysis to incorporate a simultaneity factor into district heating networks. Overall, district heating networks can reduce distribution grid reinforcements, but the associated savings alone do not justify their construction, particularly in the ambitious renovation scenario. In the business-as-usual scenario, a district heating network can reduce reinforcement costs by up to 71 %. However, in the ambitious scenario, grid reinforcements are already reduced due to lower heat peak demand, and the maximal reinforcement cost savings only amount to 35 %. Compared economically, district heating networks are cost-competitive with building-specific heating only in the business-as-usual scenario, up to a heat supply share of 70 % and in the ambitious scenario, up to 40 %. In both scenarios, a district heating network can be a robust solution to lower macroeconomic costs for a carbon-neutral heat supply.

电力、交通和供热部门之间的部门耦合增强，导致配电网升级的力度加大。基于一个案例研究，本文评估了区域供热网络在减少配电网加固方面的作用，并比较了它们与使用热泵的建筑特定供热的经济可行性。一个详细的能源系统模型被用来分析两种建筑能源改造方案：一种是常规方案，年翻新率为1%，另一种是雄心勃勃的方案，年翻新率为2%。采用两步优化，评估了不同区域供热网络渗透水平对配电网的影响，然后进行了事后分析，将同步因素纳入区域供热网络。总的来说，区域供热网络可以减少配电网的加固，但相关的节省本身并不能证明其建设的合理性，特别是在雄心勃勃的改造方案中。在一切照旧的情况下，区域供热网络可以减少高达71%的加固成本。然而，在雄心勃勃的情况下，由于较低的热峰值需求，网格加固已经减少，并且最大加固成本节约仅达35%。与经济相比，区域供热网络只有在一切照旧的情况下才具有成本竞争力，供热份额高达70%，而在雄心勃勃的情况下，则高达40%。在这两种情况下，区域供热网络都可以成为降低碳中性供热宏观经济成本的有力解决方案。

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引用次数: 0

Variability of technology learning rates 技术学习率的可变性

IF 13.8 Q1 ENERGY & FUELS

Advances in Applied Energy

Pub Date : 2025-10-28 DOI: 10.1016/j.adapen.2025.100252

Angelo Carlino , Alicia Wongel , Lei Duan , Edgar Virgüez , Steven J. Davis , Morgan R. Edwards , Ken Caldeira

Climate and energy policy analysts and researchers often forecast the cost of low-carbon energy technologies using Wright’s model of technological innovation. The learning rate, i.e., the percentage cost reduction per doubling of cumulative production, is assumed constant in this model. Here, we analyze the relationship between cost and scale of production for 87 technologies in the Performance Curve Database spanning multiple sectors. We find that stepwise changes in learning rates provide a better fit for 58 of these technologies and produce forecasts with equal or significantly lower errors compared to constant learning rates for 36 and 30 technologies, respectively. While costs generally decrease with increasing production, past learning rates are not good predictors of future learning rates. We show that these results affect technological change projections in the short and long term, focusing on three key mitigation technologies: solar photovoltaics, wind power, and lithium-ion batteries. We suggest that investment in early-stage technologies nearing cost-competitiveness, combined with techno-economic analysis and decision-making under uncertainty methods, can help mitigate the impact of uncertainty in projections of future technology cost.

气候和能源政策分析师和研究人员经常使用赖特的技术创新模型来预测低碳能源技术的成本。在这个模型中，学习率，即每增加一倍的累积产量所降低的成本百分比，被假设为常数。在此，我们分析了跨越多个行业的87种技术的成本与生产规模之间的关系。我们发现，与36种和30种技术的恒定学习率相比，学习率的逐步变化为其中58种技术提供了更好的拟合，并产生了误差相等或显着更低的预测。虽然成本通常随着产量的增加而降低，但过去的学习率并不能很好地预测未来的学习率。我们表明，这些结果会影响短期和长期的技术变化预测，重点关注三种关键的缓解技术：太阳能光伏发电、风力发电和锂离子电池。我们认为，投资于接近成本竞争力的早期技术，结合不确定性方法下的技术经济分析和决策，可以帮助减轻未来技术成本预测中不确定性的影响。

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引用次数: 0

Evaluating grid stress and reliability in future electricity grids across a range of demand, generation mix, and weather trends 在各种需求、发电组合和天气趋势下评估未来电网的压力和可靠性

IF 13.8 Q1 ENERGY & FUELS

Advances in Applied Energy

Pub Date : 2025-10-19 DOI: 10.1016/j.adapen.2025.100249

Kerem Ziya Akdemir , Kendall Mongird , Cameron Bracken , Casey D. Burleyson , Jordan D. Kern , Konstantinos Oikonomou , Travis B. Thurber , Chris R. Vernon , Nathalie Voisin , Mengqi Zhao , Jennie S. Rice

The reliability of power grids in the future will depend on how system planners account for the integration of new technologies, extreme weather events, and uncertainties in demand growth from increased electrification and data centers. This study introduces an open-source, multisectoral, multiscale modeling framework that projects grid stress and reliability trends between 2020 and 2055 in the Western Interconnection of the United States. The framework integrates global to national energy-water-land dynamics with power plant siting and hourly grid operations modeling. We analyze future wholesale electricity price shocks and unserved energy events across eight scenarios spanning a range of population growth and economic change, generation mixes, and weather conditions. Our results show future grids with high percentage of non-renewable generation and strong economic growth are characterized by higher reliability and lower wholesale electricity prices than lower growth scenarios because of larger reliance on dispatchable generators and lower fossil fuel extraction costs. Scenarios with high percentage of renewable resources have lower median but more volatile wholesale electricity prices as well as more frequent and severe unserved energy events compared to scenarios relying more on dispatchable generators. These events occur because higher proportion of solar and wind energy causes net demand curves to deepen during midday (duck curves get progressively severe), exacerbating the challenge of meeting demand during summer evening peaks. This study suggests that robust and co-optimized transmission and energy storage planning could help maintain low wholesale electricity prices and high reliability levels in future electricity grids across uncertainties in generation mixes.

未来电网的可靠性将取决于系统规划者如何考虑新技术的集成、极端天气事件以及电气化和数据中心增加带来的需求增长的不确定性。本研究介绍了一个开源、多部门、多尺度的建模框架，该框架预测了2020年至2055年美国西部电网的电网应力和可靠性趋势。该框架将全球到国家的能源-水-土地动态与发电厂选址和每小时电网运行建模相结合。我们在人口增长、经济变化、发电组合和天气条件等八种情况下分析了未来批发电价冲击和未服务的能源事件。我们的研究结果表明，与低增长情景相比，具有高比例不可再生发电和强劲经济增长的未来电网具有更高的可靠性和更低的批发电价，因为对可调度发电机的依赖程度更高，化石燃料开采成本更低。与更多依赖可调度发电机的情景相比，可再生资源比例较高的情景电价中位数较低，但批发电价波动更大，能源供应不足的事件也更频繁、更严重。这些事件的发生是因为太阳能和风能的较高比例导致净需求曲线在中午加深（鸭曲线逐渐变得严重），加剧了满足夏季晚间高峰需求的挑战。这项研究表明，在不确定的发电组合中，强大的、协同优化的输电和储能规划可以帮助在未来电网中保持低批发电价和高可靠性水平。

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